2023

A. Mayr, S. Lehner, A. Mayrhofer, C. Kloss, S. Hochreiter, and J. Brandstetter (2023) Boundary Graph Neural Networks for 3D Simulations. Proceedings of the AAAI Conference on Artificial Intelligence, 37, 8, 9099-9107, 2023-06-26. (more) (download)

B. Schäfl, L. Gruber, J. Brandstetter, and S. Hochreiter (2023) G-Signatures: Global Graph Propagation with Randomized Signatures. arXiv:2302.08811, 2023-02-17. (more) (download)

2022

V. T. Tran, L. Lewis, H.-Y. Huang, J. Kofler, R. Kueng, S. Hochreiter, and S. Lehner (2022) Using Shadows to Learn Ground State Properties of Quantum Hamiltonians. Machine Learning and the Physical Sciences at NeurIPS 2022, 2022-12-03. (more) (download)

S. Sanokowski, W. Berghammer, J. Kofler, S. Hochreiter, and S. Lehner (2022) One Network to Approximate Them All: Amortized Variational Inference of Ising Ground States. Machine Learning and the Physical Sciences at NeurIPS 2022, 2022-12-03. (more) (download)

S. Hochreiter (2022) Toward a broad AI. Communications of the ACM, 65, 4, 56-57, 2022-03-19. (more) (download)

2021

A. Mayr, S. Lehner, A. Mayrhofer, C. Kloss, S. Hochreiter, and J. Brandstetter (2021) Learning 3D Granular Flow Simulations. arXiv: 2105.01636, 2021-05-04. (more) (download)

X. He, Y. Chen, and P. Ghamisi (2021) Dual Graph Convolutional Network for Hyperspectral Image Classification with Limited Training Samples. IEEE Transactions on Geoscience and Remote Sensing, 2021-03-08. (more) (download)

F. Kratzert, D. Klotz, M. Gauch, C. Klingler, G. Nearing, and S. Hochreiter (2021) Large-Scale River Network Modeling Using Graph Neural Networks. EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13375, 2021-03-03. (more) (download)

2020

H. Martin, D. Bucher, Y. Hong, R. Buffat, C. Rupprecht, and M. Raubal (2020) Graph-ResNets for short-term traffic forecasts in almost unknown cities. Proceedings of the NeurIPS 2019 Competition and Demonstration Track, PMLR 123, 153-163, 2020-08-19. (more) (download)

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